title
stringlengths
7
239
abstract
stringlengths
7
2.76k
cs
int64
0
1
phy
int64
0
1
math
int64
0
1
stat
int64
0
1
quantitative biology
int64
0
1
quantitative finance
int64
0
1
Exploring cosmic origins with CORE: mitigation of systematic effects
We present an analysis of the main systematic effects that could impact the measurement of CMB polarization with the proposed CORE space mission. We employ timeline-to-map simulations to verify that the CORE instrumental set-up and scanning strategy allow us to measure sky polarization to a level of accuracy adequate...
0
1
0
0
0
0
A non-ordinary peridynamics implementation for anisotropic materials
Peridynamics (PD) represents a new approach for modelling fracture mechanics, where a continuum domain is modelled through particles connected via physical bonds. This formulation allows us to model crack initiation, propagation, branching and coalescence without special assumptions. Up to date, anisotropic materials...
1
1
0
0
0
0
Discrete-attractor-like Tracking in Continuous Attractor Neural Networks
Continuous attractor neural networks generate a set of smoothly connected attractor states. In memory systems of the brain, these attractor states may represent continuous pieces of information such as spatial locations and head directions of animals. However, during the replay of previous experiences, hippocampal ne...
0
0
0
0
1
0
Framework for an Innovative Perceptive Mobile Network Using Joint Communication and Sensing
In this paper, we develop a framework for an innovative perceptive mobile (i.e. cellular) network that integrates sensing with communication, and supports new applications widely in transportation, surveillance and environmental sensing. Three types of sensing methods implemented in the base-stations are proposed, us...
1
0
0
0
0
0
On the smallest non-abelian quotient of $\mathrm{Aut}(F_n)$
We show that the smallest non-abelian quotient of $\mathrm{Aut}(F_n)$ is $\mathrm{PSL}_n(\mathbb{Z}/2\mathbb{Z}) = \mathrm{L}_n(2)$, thus confirming a conjecture of Mecchia--Zimmermann. In the course of the proof we give an exponential (in $n$) lower bound for the cardinality of a set on which $\mathrm{SAut}(F_n)$, t...
0
0
1
0
0
0
Property Testing in High Dimensional Ising models
This paper explores the information-theoretic limitations of graph property testing in zero-field Ising models. Instead of learning the entire graph structure, sometimes testing a basic graph property such as connectivity, cycle presence or maximum clique size is a more relevant and attainable objective. Since proper...
0
0
1
1
0
0
Stratification and duality for homotopical groups
In this paper, we show that the category of module spectra over $C^*(B\mathcal{G},\mathbb{F}_p)$ is stratified for any $p$-local compact group $\mathcal{G}$, thereby giving a support-theoretic classification of all localizing subcategories of this category. To this end, we generalize Quillen's $F$-isomorphism theorem...
0
0
1
0
0
0
Efficiently and easily integrating differential equations with JiTCODE, JiTCDDE, and JiTCSDE
We present a family of Python modules for the numerical integration of ordinary, delay, or stochastic differential equations. The key features are that the user enters the derivative symbolically and it is just-in-time-compiled, allowing the user to efficiently integrate differential equations from a higher-level int...
1
1
0
0
0
0
Adaptive Diffusions for Scalable Learning over Graphs
Diffusion-based classifiers such as those relying on the Personalized PageRank and the Heat kernel, enjoy remarkable classification accuracy at modest computational requirements. Their performance however is affected by the extent to which the chosen diffusion captures a typically unknown label propagation mechanism,...
0
0
0
1
0
0
On the Discrimination Power and Effective Utilization of Active Learning Measures in Version Space Search
Active Learning (AL) methods have proven cost-saving against passive supervised methods in many application domains. An active learner, aiming to find some target hypothesis, formulates sequential queries to some oracle. The set of hypotheses consistent with the already answered queries is called version space. Sever...
1
0
0
0
0
0
Torchbearer: A Model Fitting Library for PyTorch
We introduce torchbearer, a model fitting library for pytorch aimed at researchers working on deep learning or differentiable programming. The torchbearer library provides a high level metric and callback API that can be used for a wide range of applications. We also include a series of built in callbacks that can be...
0
0
0
1
0
0
On estimation of contamination from hydrogen cyanide in carbon monoxide line intensity mapping
Line-intensity mapping surveys probe large-scale structure through spatial variations in molecular line emission from a population of unresolved cosmological sources. Future such surveys of carbon monoxide line emission, specifically the CO(1-0) line, face potential contamination from a disjoint population of sources...
0
1
0
0
0
0
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
Classifiers can be trained with data-dependent constraints to satisfy fairness goals, reduce churn, achieve a targeted false positive rate, or other policy goals. We study the generalization performance for such constrained optimization problems, in terms of how well the constraints are satisfied at evaluation time, ...
0
0
0
1
0
0
Automated Website Fingerprinting through Deep Learning
Several studies have shown that the network traffic that is generated by a visit to a website over Tor reveals information specific to the website through the timing and sizes of network packets. By capturing traffic traces between users and their Tor entry guard, a network eavesdropper can leverage this meta-data to...
1
0
0
0
0
0
DataCite as a novel bibliometric source: Coverage, strengths and limitations
This paper explores the characteristics of DataCite to determine its possibilities and potential as a new bibliometric data source to analyze the scholarly production of open data. Open science and the increasing data sharing requirements from governments, funding bodies, institutions and scientific journals has led ...
1
0
0
0
0
0
Parameter Estimation of Complex Fractional Ornstein-Uhlenbeck Processes with Fractional Noise
We obtain strong consistency and asymptotic normality of a least squares estimator of the drift coefficient for complex-valued Ornstein-Uhlenbeck processes disturbed by fractional noise, extending the result of Y. Hu and D. Nualart, [Statist. Probab. Lett., 80 (2010), 1030-1038] to a special 2-dimensions. The strateg...
0
0
1
1
0
0
E-learning Information Technology Based on an Ontology Driven Learning Engine
In the article, proposed is a new e-learning information technology based on an ontology driven learning engine, which is matched with modern pedagogical technologies. With the help of proposed engine and developed question database we have conducted an experiment, where students were tested. The developed ontology d...
1
0
0
0
0
0
Global regularity for 1D Eulerian dynamics with singular interaction forces
The Euler-Poisson-Alignment (EPA) system appears in mathematical biology and is used to model, in a hydrodynamic limit, a set agents interacting through mutual attraction/repulsion as well as alignment forces. We consider one-dimensional EPA system with a class of singular alignment terms as well as natural attractio...
0
0
1
0
0
0
A $q$-generalization of the para-Racah polynomials
New bispectral orthogonal polynomials are obtained from an unconventional truncation of the Askey-Wilson polynomials. In the limit $q \to 1$, they reduce to the para-Racah polynomials which are orthogonal with respect to a quadratic bi-lattice. The three term recurrence relation and q-difference equation are obtained...
0
0
1
0
0
0
Data Poisoning Attack against Unsupervised Node Embedding Methods
Unsupervised node embedding methods (e.g., DeepWalk, LINE, and node2vec) have attracted growing interests given their simplicity and effectiveness. However, although these methods have been proved effective in a variety of applications, none of the existing work has analyzed the robustness of them. This could be very...
1
0
0
0
0
0
Entanglement properties of the two-dimensional SU(3) AKLT state
Two-dimensional (spin-$2$) Affleck-Kennedy-Lieb-Tasaki (AKLT) type valence bond solids on the square lattice are known to be symmetry protected topological (SPT) gapped spin liquids [Shintaro Takayoshi, Pierre Pujol, and Akihiro Tanaka Phys. Rev. B ${\bf 94}$, 235159 (2016)]. Using the projected entangled pair state ...
0
1
0
0
0
0
Heart Rate Variability during Periods of Low Blood Pressure as a Predictor of Short-Term Outcome in Preterms
Efficient management of low blood pressure (BP) in preterm neonates remains challenging with a considerable variability in clinical practice. The ability to assess preterm wellbeing during episodes of low BP will help to decide when and whether hypotension treatment should be initiated. This work aims to investigate ...
0
0
0
1
0
0
Understanding News Outlets' Audience-Targeting Patterns
The power of the press to shape the informational landscape of a population is unparalleled, even now in the era of democratic access to all information outlets. However, it is known that news outlets (particularly more traditional ones) tend to discriminate who they want to reach, and who to leave aside. In this wor...
1
0
0
0
0
0
Deriving a Representative Vector for Ontology Classes with Instance Word Vector Embeddings
Selecting a representative vector for a set of vectors is a very common requirement in many algorithmic tasks. Traditionally, the mean or median vector is selected. Ontology classes are sets of homogeneous instance objects that can be converted to a vector space by word vector embeddings. This study proposes a method...
1
0
0
0
0
0
The ESA Gaia Archive: Data Release 1
ESA Gaia mission is producing the more accurate source catalogue in astronomy up to now. That represents a challenge on the archiving area to make accessible this information to the astronomers in an efficient way. Also, new astronomical missions have reinforced the change on the development of archives. Archives, as...
0
1
0
0
0
0
Efficient algorithm for large spectral partitions
We present an amelioration of current known algorithms for optimal spectral partitioning problems. The idea is to use the advantage of a representation using density functions while decreasing the computational time. This is done by restricting the computation to neighbourhoods of regions where the associated densiti...
0
0
1
0
0
0
A Martian Origin for the Mars Trojan Asteroids
Seven of the nine known Mars Trojan asteroids belong to an orbital cluster named after its largest member 5261 Eureka. Eureka is likely the progenitor of the whole cluster, which formed at least 1 Gyr ago. It was suggested that the thermal YORP effect spun-up Eureka resulting with fragments being ejected by the rotat...
0
1
0
0
0
0
Far-infrared metallicity diagnostics: Application to local ultraluminous infrared galaxies
The abundance of metals in galaxies is a key parameter which permits to distinguish between different galaxy formation and evolution models. Most of the metallicity determinations are based on optical line ratios. However, the optical spectral range is subject to dust extinction and, for high-z objects (z > 3), some ...
0
1
0
0
0
0
Quantum communication by means of collapse of the wave function
We show that quantum communication by means of collapse of the wave function is possible. In this study, quantum communication does not mean quantum teleportation or quantum cryptography, but transmission of information itself. Because of consistency with special relativity, the possibility of the quantum communicati...
0
1
0
0
0
0
DeepTerramechanics: Terrain Classification and Slip Estimation for Ground Robots via Deep Learning
Terramechanics plays a critical role in the areas of ground vehicles and ground mobile robots since understanding and estimating the variables influencing the vehicle-terrain interaction may mean the success or the failure of an entire mission. This research applies state-of-the-art algorithms in deep learning to two...
1
0
0
0
0
0
Characterizations of multinormality and corresponding tests of fit, including for Garch models
We provide novel characterizations of multivariate normality that incorporate both the characteristic function and the moment generating function, and we employ these results to construct a class of affine invariant, consistent and easy-to-use goodness-of-fit tests for normality. The test statistics are suitably weig...
0
0
1
1
0
0
Grouped Gaussian Processes for Solar Power Prediction
We consider multi-task regression models where the observations are assumed to be a linear combination of several latent node functions and weight functions, which are both drawn from Gaussian process priors. Driven by the problem of developing scalable methods for forecasting distributed solar and other renewable po...
0
0
0
1
0
0
Modeling epidemics on d-cliqued graphs
Since social interactions have been shown to lead to symmetric clusters, we propose here that symmetries play a key role in epidemic modeling. Mathematical models on d-ary tree graphs were recently shown to be particularly effective for modeling epidemics in simple networks [Seibold & Callender, 2016]. To account for...
1
0
0
0
1
0
On the K-theory stable bases of the Springer resolution
Cohomological and K-theoretic stable bases originated from the study of quantum cohomology and quantum K-theory. Restriction formula for cohomological stable bases played an important role in computing the quantum connection of cotangent bundle of partial flag varieties. In this paper we study the K-theoretic stable ...
0
0
1
0
0
0
Recency Bias in the Era of Big Data: The Need to Strengthen the Status of History of Mathematics in Nigerian Schools
The amount of information available to the mathematics teacher is so enormous that the selection of desirable content is gradually becoming a huge task in itself. With respect to the inclusion of elements of history of mathematics in mathematics instruction, the era of Big Data introduces a high likelihood of Recency...
1
0
1
0
0
0
Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings
This paper presents a convergence analysis of kernel-based quadrature rules in misspecified settings, focusing on deterministic quadrature in Sobolev spaces. In particular, we deal with misspecified settings where a test integrand is less smooth than a Sobolev RKHS based on which a quadrature rule is constructed. We ...
1
0
0
1
0
0
The toric Frobenius morphism and a conjecture of Orlov
We combine the Bondal-Uehara method for producing exceptional collections on toric varieties with a result of the first author and Favero to expand the set of varieties satisfying Orlov's Conjecture on derived dimension.
0
0
1
0
0
0
Friendship Maintenance and Prediction in Multiple Social Networks
Due to the proliferation of online social networks (OSNs), users find themselves participating in multiple OSNs. These users leave their activity traces as they maintain friendships and interact with other users in these OSNs. In this work, we analyze how users maintain friendship in multiple OSNs by studying users w...
1
1
0
0
0
0
Learning to Generate Music with BachProp
As deep learning advances, algorithms of music composition increase in performance. However, most of the successful models are designed for specific musical structures. Here, we present BachProp, an algorithmic composer that can generate music scores in many styles given sufficient training data. To adapt BachProp to...
1
0
0
0
0
0
How to Quantize $n$ Outputs of a Binary Symmetric Channel to $n-1$ Bits?
Suppose that $Y^n$ is obtained by observing a uniform Bernoulli random vector $X^n$ through a binary symmetric channel with crossover probability $\alpha$. The "most informative Boolean function" conjecture postulates that the maximal mutual information between $Y^n$ and any Boolean function $\mathrm{b}(X^n)$ is atta...
1
0
1
0
0
0
Semi-Supervised Deep Learning for Monocular Depth Map Prediction
Supervised deep learning often suffers from the lack of sufficient training data. Specifically in the context of monocular depth map prediction, it is barely possible to determine dense ground truth depth images in realistic dynamic outdoor environments. When using LiDAR sensors, for instance, noise is present in the...
1
0
0
0
0
0
Approximation Schemes for Clustering with Outliers
Clustering problems are well-studied in a variety of fields such as data science, operations research, and computer science. Such problems include variants of centre location problems, $k$-median, and $k$-means to name a few. In some cases, not all data points need to be clustered; some may be discarded for various r...
1
0
0
0
0
0
Order preserving pattern matching on trees and DAGs
The order preserving pattern matching (OPPM) problem is, given a pattern string $p$ and a text string $t$, find all substrings of $t$ which have the same relative orders as $p$. In this paper, we consider two variants of the OPPM problem where a set of text strings is given as a tree or a DAG. We show that the OPPM p...
1
0
0
0
0
0
Categorical Probabilistic Theories
We present a simple categorical framework for the treatment of probabilistic theories, with the aim of reconciling the fields of Categorical Quantum Mechanics (CQM) and Operational Probabilistic Theories (OPTs). In recent years, both CQM and OPTs have found successful application to a number of areas in quantum found...
0
0
1
0
0
0
Maximal polynomial modulations of singular integrals
Let $K$ be a standard Hölder continuous Calderón--Zygmund kernel on $\mathbb{R}^{\mathbf{d}}$ whose truncations define $L^2$ bounded operators. We show that the maximal operator obtained by modulating $K$ by polynomial phases of a fixed degree is bounded on $L^p(\mathbb{R}^{\mathbf{d}})$ for $1 < p < \infty$. This ex...
0
0
1
0
0
0
Effects of Hubbard term correction on the structural parameters and electronic properties of wurtzite Zn
The effects of including the Hubbard on-site Coulombic correction to the structural parameters and valence energy states of wurtzite ZnO was explored. Due to the changes in the structural parameters caused by correction of hybridization between Zn d states and O p states, suitable parameters of Hubbard terms have to ...
0
1
0
0
0
0
A multi-scale Gaussian beam parametrix for the wave equation: the Dirichlet boundary value problem
We present a construction of a multi-scale Gaussian beam parametrix for the Dirichlet boundary value problem associated with the wave equation, and study its convergence rate to the true solution in the highly oscillatory regime. The construction elaborates on the wave-atom parametrix of Bao, Qian, Ying, and Zhang an...
0
0
1
0
0
0
Uncertainty and sensitivity analysis of functional risk curves based on Gaussian processes
A functional risk curve gives the probability of an undesirable event as a function of the value of a critical parameter of a considered physical system. In several applicative situations, this curve is built using phenomenological numerical models which simulate complex physical phenomena. To avoid cpu-time expensiv...
0
0
1
1
0
0
Global optimization for low-dimensional switching linear regression and bounded-error estimation
The paper provides global optimization algorithms for two particularly difficult nonconvex problems raised by hybrid system identification: switching linear regression and bounded-error estimation. While most works focus on local optimization heuristics without global optimality guarantees or with guarantees valid on...
1
0
0
1
0
0
An Incremental Self-Organizing Architecture for Sensorimotor Learning and Prediction
During visuomotor tasks, robots must compensate for temporal delays inherent in their sensorimotor processing systems. Delay compensation becomes crucial in a dynamic environment where the visual input is constantly changing, e.g., during the interacting with a human demonstrator. For this purpose, the robot must be ...
1
0
0
0
0
0
A CutFEM method for two-phase flow problems
In this article, we present a cut finite element method for two-phase Navier-Stokes flows. The main feature of the method is the formulation of a unified continuous interior penalty stabilisation approach for, on the one hand, stabilising advection and the pressure-velocity coupling and, on the other hand, stabilisin...
1
0
0
0
0
0
Learning under selective labels in the presence of expert consistency
We explore the problem of learning under selective labels in the context of algorithm-assisted decision making. Selective labels is a pervasive selection bias problem that arises when historical decision making blinds us to the true outcome for certain instances. Examples of this are common in many applications, rang...
0
0
0
1
0
0
Opacity limit for supermassive protostars
We present a model for the evolution of supermassive protostars from their formation at $M_\star \simeq 0.1\,\text{M}_\odot$ until their growth to $M_\star \simeq 10^5\,\text{M}_\odot$. To calculate the initial properties of the object in the optically thick regime we follow two approaches: based on idealized thermod...
0
1
0
0
0
0
Learning to Imagine Manipulation Goals for Robot Task Planning
Prospection is an important part of how humans come up with new task plans, but has not been explored in depth in robotics. Predicting multiple task-level is a challenging problem that involves capturing both task semantics and continuous variability over the state of the world. Ideally, we would combine the ability ...
1
0
0
0
0
0
On the Combinatorial Power of the Weisfeiler-Lehman Algorithm
The classical Weisfeiler-Lehman method WL[2] uses edge colors to produce a powerful graph invariant. It is at least as powerful in its ability to distinguish non-isomorphic graphs as the most prominent algebraic graph invariants. It determines not only the spectrum of a graph, and the angles between standard basis ve...
1
0
0
0
0
0
Learning to Generate Reviews and Discovering Sentiment
We explore the properties of byte-level recurrent language models. When given sufficient amounts of capacity, training data, and compute time, the representations learned by these models include disentangled features corresponding to high-level concepts. Specifically, we find a single unit which performs sentiment an...
1
0
0
0
0
0
Designing magnetism in Fe-based Heusler alloys: a machine learning approach
Combining material informatics and high-throughput electronic structure calculations offers the possibility of a rapid characterization of complex magnetic materials. Here we demonstrate that datasets of electronic properties calculated at the ab initio level can be effectively used to identify and understand physica...
0
1
0
0
0
0
On a diffuse interface model for tumour growth with non-local interactions and degenerate mobilities
We study a non-local variant of a diffuse interface model proposed by Hawkins--Darrud et al. (2012) for tumour growth in the presence of a chemical species acting as nutrient. The system consists of a Cahn--Hilliard equation coupled to a reaction-diffusion equation. For non-degenerate mobilities and smooth potentials...
0
0
1
0
0
0
Gradient Descent Can Take Exponential Time to Escape Saddle Points
Although gradient descent (GD) almost always escapes saddle points asymptotically [Lee et al., 2016], this paper shows that even with fairly natural random initialization schemes and non-pathological functions, GD can be significantly slowed down by saddle points, taking exponential time to escape. On the other hand,...
1
0
1
1
0
0
Spectral parameter power series for arbitrary order linear differential equations
Let $L$ be the $n$-th order linear differential operator $Ly = \phi_0y^{(n)} + \phi_1y^{(n-1)} + \cdots + \phi_ny$ with variable coefficients. A representation is given for $n$ linearly independent solutions of $Ly=\lambda r y$ as power series in $\lambda$, generalizing the SPPS (spectral parameter power series) solu...
0
0
1
0
0
0
Antropologia de la Informatica Social: Teoria de la Convergencia Tecno-Social
The traditional humanism of the twentieth century, inspired by the culture of the book, systematically distanced itself from the new society of digital information; the Internet and tools of information processing revolutionized the world, society during this period developed certain adaptive characteristics based on...
1
0
0
0
0
0
A Deterministic Approach to Avoid Saddle Points
Loss functions with a large number of saddle points are one of the main obstacles to training many modern machine learning models. Gradient descent (GD) is a fundamental algorithm for machine learning and converges to a saddle point for certain initial data. We call the region formed by these initial values the "attr...
1
0
0
1
0
0
Automatic Generation of Typographic Font from a Small Font Subset
This paper addresses the automatic generation of a typographic font from a subset of characters. Specifically, we use a subset of a typographic font to extrapolate additional characters. Consequently, we obtain a complete font containing a number of characters sufficient for daily use. The automated generation of Jap...
1
0
0
0
0
0
The Second Postulate of Euclid and the Hyperbolic Geometry
The article deals with the connection between the second postulate of Euclid and non-Euclidean geometry. It is shown that the violation of the second postulate of Euclid inevitably leads to hyperbolic geometry. This eliminates misunderstandings about the sums of some divergent series. The connection between hyperboli...
0
0
1
0
0
0
Transkernel: An Executor for Commodity Kernels on Peripheral Cores
Modern mobile and embedded platforms see a large number of ephemeral tasks driven by background activities. In order to execute such a task, the OS kernel wakes up the platform beforehand and puts it back to sleep afterwards. In doing so, the kernel operates various IO devices and orchestrates their power state trans...
1
0
0
0
0
0
No iterated identities satisfied by all finite groups
We show that there is no iterated identity satisfied by all finite groups. For $w$ being a non-trivial word of length $l$, we show that there exists a finite group $G$ of cardinality at most $\exp(l^C)$ which does not satisfy the iterated identity $w$. The proof uses the approach of Borisov and Sapir, who used dynami...
0
0
1
0
0
0
Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning
The goal of this tutorial is to introduce key models, algorithms, and open questions related to the use of optimization methods for solving problems arising in machine learning. It is written with an INFORMS audience in mind, specifically those readers who are familiar with the basics of optimization algorithms, but ...
1
0
0
1
0
0
A Unified Parallel Algorithm for Regularized Group PLS Scalable to Big Data
Partial Least Squares (PLS) methods have been heavily exploited to analyse the association between two blocs of data. These powerful approaches can be applied to data sets where the number of variables is greater than the number of observations and in presence of high collinearity between variables. Different sparse ...
0
0
0
1
0
0
Asymptotic behaviour of the fifth Painlevé transcendents in the space of initial values
We study the asymptotic behaviour of the solutions of the fifth Painlevé equation as the independent variable approaches zero and infinity in the space of initial values. We show that the limit set of each solution is compact and connected and, moreover, that any solution with the essential singularity at zero has an...
0
1
1
0
0
0
Hidden Treasures - Recycling Large-Scale Internet Measurements to Study the Internet's Control Plane
Internet-wide scans are a common active measurement approach to study the Internet, e.g., studying security properties or protocol adoption. They involve probing large address ranges (IPv4 or parts of IPv6) for specific ports or protocols. Besides their primary use for probing (e.g., studying protocol adoption), we s...
1
0
0
0
0
0
Image Registration and Predictive Modeling: Learning the Metric on the Space of Diffeomorphisms
We present a method for metric optimization in the Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework, by treating the induced Riemannian metric on the space of diffeomorphisms as a kernel in a machine learning context. For simplicity, we choose the kernel Fischer Linear Discriminant Analysis (KLDA) as ...
0
0
0
1
0
0
On a direct algorithm for constructing recursion operators and Lax pairs for integrable models
We suggested an algorithm for searching the recursion operators for nonlinear integrable equations. It was observed that the recursion operator $R$ can be represented as a ratio of the form $R=L_1^{-1}L_2$ where the linear differential operators $L_1$ and $L_2$ are chosen in such a way that the ordinary differential ...
0
1
0
0
0
0
Network Classification and Categorization
To the best of our knowledge, this paper presents the first large-scale study that tests whether network categories (e.g., social networks vs. web graphs) are distinguishable from one another (using both categories of real-world networks and synthetic graphs). A classification accuracy of $94.2\%$ was achieved using ...
1
0
0
1
0
0
A Polynomial-Time Algorithm for Solving the Minimal Observability Problem in Conjunctive Boolean Networks
Many complex systems in biology, physics, and engineering include a large number of state-variables, and measuring the full state of the system is often impossible. Typically, a set of sensors is used to measure part of the state-variables. A system is called observable if these measurements allow to reconstruct the ...
1
0
1
0
0
0
The Description and Scaling Behavior for the Inner Region of the Boundary Layer for 2-D Wall-bounded Flows
A second derivative-based moment method is proposed for describing the thickness and shape of the region where viscous forces are dominant in turbulent boundary layer flows. Rather than the fixed location sublayer model presently employed, the new method defines thickness and shape parameters that are experimentally ...
0
1
0
0
0
0
Completely Sidon sets in $C^*$-algebras (New title)
A sequence in a $C^*$-algebra $A$ is called completely Sidon if its span in $A$ is completely isomorphic to the operator space version of the space $\ell_1$ (i.e. $\ell_1$ equipped with its maximal operator space structure). The latter can also be described as the span of the free unitary generators in the (full) $C^...
0
0
1
0
0
0
Conflict-Free Coloring of Planar Graphs
A conflict-free k-coloring of a graph assigns one of k different colors to some of the vertices such that, for every vertex v, there is a color that is assigned to exactly one vertex among v and v's neighbors. Such colorings have applications in wireless networking, robotics, and geometry, and are well-studied in gra...
1
0
1
0
0
0
Explicit solutions to utility maximization problems in a regime-switching market model via Laplace transforms
We study the problem of utility maximization from terminal wealth in which an agent optimally builds her portfolio by investing in a bond and a risky asset. The asset price dynamics follow a diffusion process with regime-switching coefficients modeled by a continuous-time finite-state Markov chain. We consider an inv...
0
0
0
0
0
1
Spectroscopic study of the elusive globular cluster ESO452-SC11 and its surroundings
Globular clusters (GCs) are amongst the oldest objects in the Galaxy and play a pivotal role in deciphering its early history. We present the first spectroscopic study of the GC ESO452-SC11 using the AAOmega spectrograph at medium resolution. Given the sparsity of this object and high degree of foreground contaminati...
0
1
0
0
0
0
The Fundamental Infinity-Groupoid of a Parametrized Family
Given an infinity-category C, one can naturally construct an infinity-category Fam(C) of families of objects in C indexed by infinity-groupoids. An ordinary categorical version of this construction was used by Borceux and Janelidze in the study of generalized covering maps in categorical Galois theory. In this paper,...
0
0
1
0
0
0
Leveraging Pre-Trained 3D Object Detection Models For Fast Ground Truth Generation
Training 3D object detectors for autonomous driving has been limited to small datasets due to the effort required to generate annotations. Reducing both task complexity and the amount of task switching done by annotators is key to reducing the effort and time required to generate 3D bounding box annotations. This pap...
0
0
0
1
0
0
Epidemic spreading in multiplex networks influenced by opinion exchanges on vaccination
We study the changes of opinions about vaccination together with the evolution of a disease. In our model we consider a multiplex network consisting of two layers. One of the layers corresponds to a social network where people share their opinions and influence others opinions. The social model that rules the dynamic...
0
1
0
0
0
0
CASP Solutions for Planning in Hybrid Domains
CASP is an extension of ASP that allows for numerical constraints to be added in the rules. PDDL+ is an extension of the PDDL standard language of automated planning for modeling mixed discrete-continuous dynamics. In this paper, we present CASP solutions for dealing with PDDL+ problems, i.e., encoding from PDDL+ to ...
1
0
0
0
0
0
Primordial black holes from inflaton and spectator field perturbations in a matter-dominated era
We study production of primordial black holes (PBHs) during an early matter-dominated phase. As a source of perturbations, we consider either the inflaton field with a running spectral index or a spectator field that has a blue spectrum and thus provides a significant contribution to the PBH production at small scale...
0
1
0
0
0
0
State Space Decomposition and Subgoal Creation for Transfer in Deep Reinforcement Learning
Typical reinforcement learning (RL) agents learn to complete tasks specified by reward functions tailored to their domain. As such, the policies they learn do not generalize even to similar domains. To address this issue, we develop a framework through which a deep RL agent learns to generalize policies from smaller,...
1
0
0
1
0
0
Robust Imitation of Diverse Behaviors
Deep generative models have recently shown great promise in imitation learning for motor control. Given enough data, even supervised approaches can do one-shot imitation learning; however, they are vulnerable to cascading failures when the agent trajectory diverges from the demonstrations. Compared to purely supervis...
1
0
0
0
0
0
Efficient Measurement of the Vibrational Rogue Waves by Compressive Sampling Based Wavelet Analysis
In this paper we discuss the possible usage of the compressive sampling based wavelet analysis for the efficient measurement and for the early detection of one dimensional (1D) vibrational rogue waves. We study the construction of the triangular (V-shaped) wavelet spectra using compressive samples of rogue waves that...
0
0
1
0
0
0
SceneCut: Joint Geometric and Object Segmentation for Indoor Scenes
This paper presents SceneCut, a novel approach to jointly discover previously unseen objects and non-object surfaces using a single RGB-D image. SceneCut's joint reasoning over scene semantics and geometry allows a robot to detect and segment object instances in complex scenes where modern deep learning-based methods...
1
0
0
0
0
0
An Invariant Model of the Significance of Different Body Parts in Recognizing Different Actions
In this paper, we show that different body parts do not play equally important roles in recognizing a human action in video data. We investigate to what extent a body part plays a role in recognition of different actions and hence propose a generic method of assigning weights to different body points. The approach is...
1
0
0
0
0
0
Forecasting Crime with Deep Learning
The objective of this work is to take advantage of deep neural networks in order to make next day crime count predictions in a fine-grain city partition. We make predictions using Chicago and Portland crime data, which is augmented with additional datasets covering weather, census data, and public transportation. The...
0
0
0
1
0
0
A family of compact semitoric systems with two focus-focus singularities
About 6 years ago, semitoric systems were classified by Pelayo & Vu Ngoc by means of five invariants. Standard examples are the coupled spin oscillator on $\mathbb{S}^2 \times \mathbb{R}^2$ and coupled angular momenta on $\mathbb{S}^2 \times \mathbb{S}^2$, both having exactly one focus-focus singularity. But so far t...
0
0
1
0
0
0
Mixed Threefolds Isogenous to a Product
In this paper we study \emph{threefolds isogenous to a product of mixed type} i.e. quotients of a product of three compact Riemann surfaces $C_i$ of genus at least two by the action of a finite group $G$, which is free, but not diagonal. In particular, we are interested in the systematic construction and classificati...
0
0
1
0
0
0
Discriminatory Transfer
We observe standard transfer learning can improve prediction accuracies of target tasks at the cost of lowering their prediction fairness -- a phenomenon we named discriminatory transfer. We examine prediction fairness of a standard hypothesis transfer algorithm and a standard multi-task learning algorithm, and show ...
1
0
0
1
0
0
Ultrafast relaxation of hot phonons in Graphene-hBN Heterostructures
Fast carrier cooling is important for high power graphene based devices. Strongly Coupled Optical Phonons (SCOPs) play a major role in the relaxation of photoexcited carriers in graphene. Heterostructures of graphene and hexagonal boron nitride (hBN) have shown exceptional mobility and high saturation current, which ...
0
1
0
0
0
0
Non-linear Associative-Commutative Many-to-One Pattern Matching with Sequence Variables
Pattern matching is a powerful tool which is part of many functional programming languages as well as computer algebra systems such as Mathematica. Among the existing systems, Mathematica offers the most expressive pattern matching. Unfortunately, no open source alternative has comparable pattern matching capabilitie...
1
0
0
0
0
0
Pair Background Envelopes in the SiD Detector
The beams at the ILC produce electron positron pairs due to beam-beam interactions. This note presents for the first time a study of these processes in a detailed simulation, which shows that these pair background particles appear at angles that extend to the inner layers of the detector. The full data set of pairs p...
0
1
0
0
0
0
Expansion of percolation critical points for Hamming graphs
The Hamming graph $H(d,n)$ is the Cartesian product of $d$ complete graphs on $n$ vertices. Let $m=d(n-1)$ be the degree and $V = n^d$ be the number of vertices of $H(d,n)$. Let $p_c^{(d)}$ be the critical point for bond percolation on $H(d,n)$. We show that, for $d \in \mathbb N$ fixed and $n \to \infty$, \begin{equ...
0
0
1
0
0
0
Efficiently Manifesting Asynchronous Programming Errors in Android Apps
Android, the #1 mobile app framework, enforces the single-GUI-thread model, in which a single UI thread manages GUI rendering and event dispatching. Due to this model, it is vital to avoid blocking the UI thread for responsiveness. One common practice is to offload long-running tasks into async threads. To achieve th...
1
0
0
0
0
0
AI Challenges in Human-Robot Cognitive Teaming
Among the many anticipated roles for robots in the future is that of being a human teammate. Aside from all the technological hurdles that have to be overcome with respect to hardware and control to make robots fit to work with humans, the added complication here is that humans have many conscious and subconscious ex...
1
0
0
0
0
0
Generalizing the MVW involution, and the contragredient
For certain quasi-split reductive groups $G$ over a general field $F$, we construct an automorphism $\iota_G$ of $G$ over $F$, well-defined as an element of ${\rm Aut}(G)(F)/jG(F)$ where $j:G(F) \rightarrow {\rm Aut}(G)(F)$ is the inner-conjugation action of $G(F)$ on $G$. The automorphism $\iota_G$ generalizes (alth...
0
0
1
0
0
0